Current test procedures to identify and measure streaking use an edge detection algorithm in the spatial domain to identify discontinuities in the image data and measure the change in intensity taking place over a number of pixels. A specific kernel is used to calculate gradient magnitudes at each pixel location. Based on allowed pixel deviation, the pixel locations of high gradient magnitudes are marked. A defect density test then measures localized densities of marked pixels.
A threshold is applied to determine if the gradient magnitude suggests a streak might exist. This presents a challenge when attempting to optimize test conditions for varying amounts of streaking. The lower the threshold, the more pixels will be detected, and the results become increasingly susceptible to noise, while a higher threshold may miss subtle pixels which constitute a streak. The defect density test is sensitive to the region of interest and would also be difficult to choose criteria that would be optimum for most devices. This method also allows the possibilities of false failure due to lens roll-off or edge effects. While this technique may be adequate for detecting most edges, it may not provide an accurate measurement regarding the severity of the streaking. Additionally, this method does not contain any directional information of the streak.